This invention relates to a method of extracting parameters of a diffusion model for use in a process simulator.
Generally, the process simulator calculates a semiconductor manufacturing process such as an ion implantation process or a diffusion process of impurity by a calculator and predicts a physical amount and a form or the like such as an impurity profile within a semiconductor device.
In a diffusion simulation carried out for simulating the diffusion process in the process simulator, it is very important for improvement of a simulation precision of the process simulator to precisely extract (values of) the parameters of the diffusion model. The parameters are extracted so as to establish measured values in mainly a depth direction of the impurity-profile.
Conventionally, every parameter of the diffusion model is extracted in batch by reducing errors between the parameters and the measured values by the use of a least square method.
Therefore, a conventional method of extracting parameters of a diffusion model has the following disadvantages.
Firstly, it requires a long time for extracting the parameters. This results because every parameter of the diffusion model is extracted in batch by the use of many measured values. Furthermore, when extracting another parameter for another measured value, the conventional method requires newly extracting all the parameters. Therefore, time for extracting the parameters is further increased.
Secondly, the conventional method can not extract such parameters corresponding to the extensive process conditions. This results from the cluster of an applicable scope of the extracted parameters which occurs in the case where the process conditions of the measured values which was used for extracting cluster.
Thirdly, it is difficult to optimize the parameters according to the limited process conditions. This results because sensitivities of the parameters according to the process conditions are unknown, and therefore it is unclear which parameter should be optimized.
Fourthly, the conventional method can not provide such parameters which are applicable and useful to a broad scope. For example, parameters that cannot physically exist are provided. This results because it is essentially impossible for the diffusion model to be completely simulated in physical phenomena and the parameters automatically extracted by the least square method are therefore inaccurate.
It is an object of this invention to solve the disadvantages mentioned above and to therefore provide a method of extracting parameters of a diffusion model capable of extracting accurate and useful parameters quickly.
Other objectives, features, and advantages of the invention will become apparent from the following description.
This invention is directed to a method of extracting parameters of a diffusion model from object parameters to be used in a process simulation of a semiconductor manufacturing process, the method comprising the steps of classifying the object parameters into a first through an N-th (N being a natural integer not smaller than 2) groups, the first group being used for classifying thereinto the most fundamental physical and least model-dependent parameters, the N-th group being used for classifying thereinto the least fundamental physical and most model-dependent parameters, and extracting successively the classified parameters in the first through the N-th groups in the order from the first to the N-th groups.
This invention is also directed to a method of extracting parameters of a diffusion model from object parameters to be used in a process simulation of a semiconductor manufacturing process, the method comprising the steps of making a matrix which represents an interrelation of sensitivities between process conditions and the object parameters to be extracted, and deciding an extracting order of the parameters and one of the process conditions for use in extracting each of the parameters with the use of the matrix.
This invention is further directed to a method of extracting parameters of a diffusion model from object parameters to be extracted used in a process simulation of a semiconductor manufacturing process, the method comprising the steps of classifying the object parameters into a first through an N-th (the N being a natural integer not smaller than 2) groups, the first group being used for classifying thereinto the most fundamental physical and least model-dependent parameters, the N-th group being used for classifying thereinto the least fundamental physical and most model-dependent parameters, and deciding an extracting order for extracting the classified parameters from each of the first through the N-th groups, making a matrix which represents an interrelation of sensitivities between process conditions and each of the parameters to be extracted, regarding each of the classified parameters to be extracted from each of the first through the N-th groups in the decided extracting order, deciding one of the process conditions for use in extracting each of the parameters with the use of the matrix, and extracting successively the classified parameters in the first through the N-th groups in the order from the first to the N-th group, the parameters extracting step extracts the classified parameters from each of the first through the N-th groups on the basis of the decided extracting order, so that each of the parameters satisfies each of the decided process conditions.